Basics of designing and steps of implementing cross-sectional studies in general practice and primary care^☆

Abstract

Cross-sectional study is one of the classic research design methods, widely applied across various clinical research. In general practice research, cross-sectional designs are frequently used to answer many scientific questions. These include investigations into health status and burden of disease, or need, demand and use of health services of a giving population in a specific time frame, as well as a variety of research scenarios such as the form of disease screening and diagnosis methods for groups of community. In the field of general practice, cross-sectional studies can be applied for status description, comparative analysis, correlation factor analysis, and the exploration of community-based screening diagnostic methods. Two main stages should be involved in cross-sectional studies, i.e., study design and study implementation. The design stage includes accurate extraction of study objectives, defining study population, study factors and outcome indicators, and determining the method of sample acquisition, determining the strategies of sampling and appropriate statistical analysis. In the implementation stage, sophisticated research plan and case report form should be used to present research design ideas, and data collection should be carried out under the premise of ethical approval. Meanwhile, quality of data management and statistical analysis methods in the plan should be rigorously applied for scientifically verifying default research question(s). Cross-sectional studies are advantageous due to their short duration compared to longitudinal cohort studies. They are suitable for various research teams with different backgrounds and can provide valuable insights into community health services by investigating the status of health services and exploring association factors for potential using in screening approaches that preventing health of community people.

Keywords

General practice / Primary health care / Cross-sectional studies / Investigation / Correlation analysis / Diagnostic ability evaluation / Research design

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